A global evaluation model applied to wind power plant site selection

被引:23
作者
Asadi, Meysam [1 ]
Ramezanzade, Mohsen [2 ]
Pourhossein, Kazem [1 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Tabriz Branch, Tabriz, Iran
[2] Noshirvani Univ Technol, Dept Elect & Comp Engn, Babol, Iran
关键词
Wind energy; Site selection; GIS; Full Factorial Design (FFD); AHP; Model design; DECISION-MAKING MCDM; ANALYTIC HIERARCHY PROCESS; ELECTRICITY PRODUCTION; INFORMATION-SYSTEM; FARM LOCATIONS; ENERGY; GIS; SOLAR; DESIGN; OPTIMIZATION;
D O I
10.1016/j.apenergy.2023.120840
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Site selection is one of the most critical steps in designing wind farms due to the heterogeneous distribution of wind energy on the Earth's surface. Additionally, the wind power site selection problem is a complex process since it must be evaluated from multiple perspectives, including techno-economic, social, and environmental factors. In this regard, the current study proposes a new approach which combines Full Factorial Design and Analytic Hierarchy Process. The output of this combination creates a global model for the site selection of wind power plants. Using this model, the decision-making space is transformed into the scoring space which makes the scores related to candidate sites more meaningful and understandable. Therefore, Iran is selected to find suitable wind sites to reveal the proposed model's capability. The results indicate that approximately 1300, 5109, and 16000 km2 of the study area are considered outstanding, excellent, and good for the utilization of wind energy. Furthermore, a functional analysis was conducted to ensure that the proposed model was robust, and accord-ingly, the accuracy of siting some existing wind farm sites was also studied. Based on the calculated scores, some real sites, e.g., Khaf and Manjil, are suitable for wind power development. Some sites could be more carefully selected, like the Binaloud wind site; others have not been appropriately selected, such as the Soffeh, Shiraz, and Sarab sites. Finally, the model can be employed worldwide as a standard index for assessing wind farm site quality.
引用
收藏
页数:24
相关论文
共 104 条
[11]   GIS-assisted modeling of wind farm site selection based on support vector regression [J].
Asadi, Meysam ;
Pourhossein, Kazem ;
Mohammadi-Ivatloo, Behnam .
JOURNAL OF CLEANER PRODUCTION, 2023, 390
[12]   Wind and Solar Farms Site Selection Using Geographical Information System (GIS), Based on Multi Criteria Decision Making (MCDM) Methods: A Case-Study for East-Azerbaijan [J].
Asadi, Meysam ;
PourHossein, Kazem .
2019 IRANIAN CONFERENCE ON RENEWABLE ENERGY & DISTRIBUTED GENERATION (ICREDG), 2019,
[13]   Wind farm site selection considering turbulence intensity [J].
Asadi, Meysam ;
Pourhossein, Kazem .
ENERGY, 2021, 236
[14]   Locating Renewable Energy Generators Using K-Nearest Neighbors (KNN) Algorithm [J].
Asadi, Meysam ;
Pourhossein, Kazem .
2019 IRANIAN CONFERENCE ON RENEWABLE ENERGY & DISTRIBUTED GENERATION (ICREDG), 2019,
[15]   Neural network-based modelling of wind/solar farm siting: a case study of East-Azerbaijan [J].
Asadi, Meysam ;
Pourhossein, Kazem .
INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY, 2021, 40 (07) :616-637
[16]  
Asadi M, 2019, 2019 INTERNATIONAL AEGEAN CONFERENCE ON ELECTRICAL MACHINES AND POWER ELECTRONICS (ACEMP) & 2019 INTERNATIONAL CONFERENCE ON OPTIMIZATION OF ELECTRICAL AND ELECTRONIC EQUIPMENT (OPTIM), P511, DOI [10.1109/ACEMP-OPTIM44294.2019.9007148, 10.1109/acemp-optim44294.2019.9007148]
[17]   A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria [J].
Ayodele, T. R. ;
Ogunjuyigbe, A. S. O. ;
Odigie, O. ;
Munda, J. L. .
APPLIED ENERGY, 2018, 228 :1853-1869
[18]  
Azzioui A, 2021, DYNAMIC MULTICRITERI, P92, DOI [10.5220/0010428800920102, DOI 10.5220/0010428800920102]
[19]  
Babadi AN., 2018, PROC 2018 SMART GRID, P2018, DOI [10.1109/SGC.2018.8777861, DOI 10.1109/SGC.2018.8777861]
[20]   A comprehensive approach for wind power plant potential assessment, application to northwestern Iran [J].
Bina, Saeid Moharnmadzadeh ;
Jalilinasrabady, Saeid ;
Fujii, Hikari ;
Farabi-Asl, Hadi .
ENERGY, 2018, 164 :344-358